Tutorials and case studies teaching data-scientific concepts in statistics courses.

Providing an easy way to bootstrap nested linear-mixed effects models using either the parametric, residual, cases, CGR (semi-parametric), or random effects block (REB) bootstrap fit using either lme4 or nlme.

Extending ggplot2 to provide a complete implementation of Q-Q plots.

In June I attended an ACM workshop focused on how the ACM can facilitate sharing elements of a data science curriculum across institutions. This is my recap.

The analyses that get me excited are not Google crunching a terabyte of web ad data in order to optimize revenue… [but rather] the biologists who are absolutely passionate about this one swampfly and now they can use R and they can understand it.

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